Use of RNA and genomic DNA references for inferred comparisons in DNA microarray analyses

Common Reference-Based Tandem Mass Tag Multiplexing for the Relative Quantification of Peptides: Design and Application to Degradome Analysis of Diphtheria Toxoid

Currently, animal tests are being used to confirm the potency and lack of toxicity of toxoid vaccines. In a consistency approach, animal tests could be replaced if production consistency (compared to known good products) can be proven in a panel of in vitro assays. By mimicking the in vivo antigen processing in a simplified in vitro approach, it may be possible to distinguish aberrant products from good products. To demonstrate this, heat-exposed diphtheria toxoid was subjected to partial digestion by cathepsin S (an endoprotease involved in antigen processing), and the peptide formation/degradation kinetics were mapped for various heated toxoids. To overcome the limitations associated with the very large number of samples, we used common reference-based tandem mass tag (TMT) labeling. Instead of using one label per condition with direct comparison between the set of labels, we compared multiple labeled samples to a common reference (a pooled sample containing an aliquot of each condition). In this method, the number of samples is not limited by the number of unique TMT labels. This TMT multiplexing strategy allows for a 15-fold reduction of analysis time while retaining the reliability advantage of TMT labeling over label-free quantification. The formation of the most important peptides could be followed over time and compared among several conditions. The changes in enzymatic degradation kinetics of diphtheria toxoid revealed several suitable candidate peptides for use in a quality control assay that can distinguish structurally aberrant diphtheria toxoid from compliant toxoids.

Impact of experimental noise and annotation imprecision on data quality in microarray experiments

Data quality is intrinsically influenced by design, technical, and analytical parameters. Quality parameters have not yet been well defined for gene expression analysis by microarrays, though ad interim, following recommended good experimental practice guidelines should ensure generation of reliable and reproducible data. Here we summarize essential practical recommendations for experimental design, technical considerations, feature annotation issues, and standardization efforts.

Multipurpose instantaneous microarray detection of acute encephalitis causing viruses and their expression profiles

Detection of multiple viruses is important for global analysis of gene or protein content and expression, opening up new prospects in terms of molecular and physiological systems for pathogenic diagnosis. Early diagnosis is crucial for disease treatment and control as it reduces inappropriate use of antiviral therapy and focuses surveillance activity. This requires the ability to detect and accurately diagnose infection at or close to the source/outbreak with minimum delay and the need for specific, accessible point-of-care diagnosis able to distinguish causative viruses and their subtypes. None of the available viral diagnostic assays combine a point-of-care format with the complex capability to identify a large range of human and animal viruses. Microarray detection provides a useful, labor-saving tool for detection of multiple viruses with several advantages, such as convenience and prevention of cross-contamination of polymerase chain reaction (PCR) products, which is of foremost importance in such applications. Recently, real-time PCR assays with the ability to confirm the amplification product and quantitate the target concentration have been developed. Furthermore, nucleotide sequence analysis of amplification products has facilitated epidemiological studies of infectious disease outbreaks and monitoring of treatment outcomes for infections, in particular for viruses that mutate at high frequency. This review discusses applications of microarray technology as a potential new tool for detection and identification of acute encephalitis-causing viruses in human serum, plasma, and cell cultures.

Computational Strategies for Analyzing Data in Gene Expression Microarray Experiments

Microarray analysis has become a widely used method for generating gene expression data on a genomic scale. Microarrays have been enthusiastically applied in many fields of biological research, even though several open questions remain about the analysis of such data. A wide range of approaches are available for computational analysis, but no general consensus exists as to standard for microarray data analysis protocol. Consequently, the choice of data analysis technique is a crucial element depending both on the data and on the goals of the experiment. Therefore, basic understanding of bioinformatics is required for optimal experimental design and meaningful interpretation of the results. This review summarizes some of the common themes in DNA microarray data analysis, including data normalization and detection of differential expression. Algorithms are demonstrated by analyzing cDNA microarray data from an experiment monitoring gene expression in T helper cells. Several computational biology strategies, along with their relative merits, are overviewed and potential areas for additional research discussed. The goal of the review is to provide a computational framework for applying and evaluating such bioinformatics strategies. Solid knowledge of microarray informatics contributes to the implementation of more efficient computational protocols for the given data obtained through microarray experiments.

Role of SPI-1 secreted effectors in acute bovine response to Salmonella enterica Serovar Typhimurium: a systems biology analysis approach

Salmonella enterica Serovar Typhimurium (S. Typhimurium) causes enterocolitis with diarrhea and polymorphonuclear cell (PMN) influx into the intestinal mucosa in humans and calves. The Salmonella Type III Secretion System (T3SS) encoded at Pathogenicity Island I translocates Salmonella effector proteins SipA, SopA, SopB, SopD, and SopE2 into epithelial cells and is required for induction of diarrhea. These effector proteins act together to induce intestinal fluid secretion and transcription of C-X-C chemokines, recruiting PMNs to the infection site. While individual molecular interactions of the effectors with cultured host cells have been characterized, their combined role in intestinal fluid secretion and inflammation is less understood. We hypothesized that comparison of the bovine intestinal mucosal response to wild type Salmonella and a SipA, SopABDE2 effector mutant relative to uninfected bovine ileum would reveal heretofore unidentified diarrhea-associated host cellular pathways. To determine the coordinated effects of these virulence factors, a bovine ligated ileal loop model was used to measure responses to wild type S. Typhimurium (WT) and a ΔsipA, sopABDE2 mutant (MUT) across 12 hours of infection using a bovine microarray. Data were analyzed using standard microarray analysis and a dynamic bayesian network modeling approach (DBN). Both analytical methods confirmed increased expression of immune response genes to Salmonella infection and novel gene expression. Gene expression changes mapped to 219 molecular interaction pathways and 1620 gene ontology groups. Bayesian network modeling identified effects of infection on several interrelated signaling pathways including MAPK, Phosphatidylinositol, mTOR, Calcium, Toll-like Receptor, CCR3, Wnt, TGF-β, and Regulation of Actin Cytoskeleton and Apoptosis that were used to model of host-pathogen interactions. Comparison of WT and MUT demonstrated significantly different patterns of host response at early time points of infection (15 minutes, 30 minutes and one hour) within phosphatidylinositol, CCR3, Wnt, and TGF-β signaling pathways and the regulation of actin cytoskeleton pathway.

The Hydrogenase Chip: a tiling oligonucleotide DNA microarray technique for characterizing hydrogen-producing and -consuming microbes in microbial communities

We developed a broad-ranging method for identifying key hydrogen-producing and consuming microorganisms through analysis of hydrogenase gene content and expression in complex anaerobic microbial communities. The method is based on a tiling hydrogenase gene oligonucleotide DNA microarray (Hydrogenase Chip), which implements a high number of probes per gene by tiling probe sequences across genes of interest at 1.67 × -2 × coverage. This design favors the avoidance of false positive gene identification in samples of DNA or RNA extracted from complex microbial communities. We applied this technique to interrogate interspecies hydrogen transfer in complex communities in (i) lab-scale reductive dehalogenating microcosms enabling us to delineate key H(2)-consuming microorganisms, and (ii) hydrogen-generating microbial mats where we found evidence for significant H(2) production by cyanobacteria. Independent quantitative PCR analysis on selected hydrogenase genes showed that this Hydrogenase Chip technique is semiquantitative. We also determined that as microbial community complexity increases, specificity must be traded for sensitivity in analyzing data from tiling DNA microarrays.

Oligonucleotide microarrays for bacteriophage expression studies

Gene expression microarrays offer the ability to monitor the expression of all phage genes over an infection cycle. However, there are relatively few reports to date of microarrays being used to investigate phage biology. This chapter aims to provide an overview of how to design and implement a microarray experiment to investigate phage biology. Given the nature of microarrays being specific to an organism, each will provide a number of unique issues. In this chapter, we outline the basic theory behind microarrays and provide details on how to implement a microarray experiment from the design of oligonucleotide probes through to the hybridisation of microarrays. The matter of designing oligonucleotide probes will be discussed with regards to how probe length, secondary structure, free energy, probe orientation and amplification all have to be taken into account. As means of an example, the conditions used for the hybridisation of an array designed to be specific to the cyanophage S-PM2 is detailed.

Assessment of data processing to improve reliability of microarray experiments using genomic DNA reference

Background

Using genomic DNA as common reference in microarray experiments has recently been tested by different laboratories. Conflicting results have been reported with regard to the reliability of microarray results using this method. To explain it, we hypothesize that data processing is a critical element that impacts the data quality.

Results

Microarray experiments were performed in a γ-proteobacterium Shewanella oneidensis. Pair-wise comparison of three experimental conditions was obtained either with two labeled cDNA samples co-hybridized to the same array, or by employing Shewanella genomic DNA as a standard reference. Various data processing techniques were exploited to reduce the amount of inconsistency between both methods and the results were assessed. We discovered that data quality was significantly improved by imposing the constraint of minimal number of replicates, logarithmic transformation and random error analyses.

Conclusion

These findings demonstrate that data processing significantly influences data quality, which provides an explanation for the conflicting evaluation in the literature. This work could serve as a guideline for microarray data analysis using genomic DNA as a standard reference.

Conservation of the links between gene transcription and chromosomal organization in the highly reduced genome of Buchnera aphidicola

BACKGROUND

Genomic studies on bacteria have clearly shown the existence of chromosomal organization as regards, for example, to gene localization, order and orientation. Moreover, transcriptomic analyses have demonstrated that, in free-living bacteria, gene transcription levels and chromosomal organization are mutually influenced. We have explored the possible conservation of relationships between mRNA abundances and chromosomal organization in the highly reduced genome of Buchnera aphidicola, the primary endosymbiont of the aphids, and a close relative to Escherichia coli.

RESULTS

Using an oligonucleotide-based microarray, we normalized the transcriptomic data by genomic DNA signals in order to have access to inter-gene comparison data. Our analysis showed that mRNA abundances, gene organization (operon) and gene essentiality are correlated in Buchnera (i.e., the most expressed genes are essential genes organized in operons) whereas no link between mRNA abundances and gene strand bias was found. The effect of Buchnera genome evolution on gene expression levels has also been analysed in order to assess the constraints imposed by the obligate symbiosis with aphids, underlining the importance of some gene sets for the survival of the two partners. Finally, our results show the existence of spatial periodic transcriptional patterns in the genome of Buchnera.

CONCLUSION

Despite an important reduction in its genome size and an apparent decay of its capacity for regulating transcription, this work reveals a significant correlation between mRNA abundances and chromosomal organization of the aphid-symbiont Buchnera.

Toward genomic cell culture engineering

Genomic and proteomic based global gene expression profiling has altered the landscape of biological research in the past few years. Its potential impact on cell culture bioprocessing has only begun to emanate, partly due to the lack of genomic sequence information for the most widely used industrial cells, Chinese hamster ovary (CHO) cells. Transcriptome and proteome profiling work for species lacking extensive genomic resources must rely on information for other related species or on data obtained from expressed sequence tag (EST) sequencing projects, for which burgeoning efforts have only recently begun. This article discusses the aspects of EST sequencing in those industrially important, genomic resources-poor cell lines, articulates some of the unique features in employing microarray in the study of cultured cells, and highlights the infrastructural needs in establishing a platform for genomics based cell culture research. Recent experience has revealed that generally, most changes in culture conditions only elicit a moderate level of alteration in gene expression. Nevertheless, by broadening the conventional scope of microarray analysis to consider estimated levels of transcript abundance, much physiological insight can be gained. Examples of the application of microarray in cell culture are discussed, and the utility of pattern identification and process diagnosis are highlighted. As genomic resources continue to expand, the power of genomic tools in cell culture processing research will be amply evident. The key to harnessing the immense benefit of these genomic resources resides in the development of physiological understanding from their application.

Evaluation of reference-based two-color methods for measurement of gene expression ratios using spotted cDNA microarrays

BACKGROUND

Spotted cDNA microarrays generally employ co-hybridization of fluorescently-labeled RNA targets to produce gene expression ratios for subsequent analysis. Direct comparison of two RNA samples in the same microarray provides the highest level of accuracy; however, due to the number of combinatorial pair-wise comparisons, the direct method is impractical for studies including large number of individual samples (e.g., tumor classification studies). For such studies, indirect comparisons using a common reference standard have been the preferred method. Here we evaluated the precision and accuracy of reconstructed ratios from three indirect methods relative to ratios obtained from direct hybridizations, herein considered as the gold-standard.

RESULTS

We performed hybridizations using a fixed amount of Cy3-labeled reference oligonucleotide (RefOligo) against distinct Cy5-labeled targets from prostate, breast and kidney tumor samples. Reconstructed ratios between all tissue pairs were derived from ratios between each tissue sample and RefOligo. Reconstructed ratios were compared to (i) ratios obtained in parallel from direct pair-wise hybridizations of tissue samples, and to (ii) reconstructed ratios derived from hybridization of each tissue against a reference RNA pool (RefPool). To evaluate the effect of the external references, reconstructed ratios were also calculated directly from intensity values of single-channel (One-Color) measurements derived from tissue sample data collected in the RefOligo experiments. We show that the average coefficient of variation of ratios between intra- and inter-slide replicates derived from RefOligo, RefPool and One-Color were similar and 2 to 4-fold higher than ratios obtained in direct hybridizations. Correlation coefficients calculated for all three tissue comparisons were also similar. In addition, the performance of all indirect methods in terms of their robustness to identify genes deemed as differentially expressed based on direct hybridizations, as well as false-positive and false-negative rates, were found to be comparable.

CONCLUSION

RefOligo produces ratios as precise and accurate as ratios reconstructed from a RNA pool, thus representing a reliable alternative in reference-based hybridization experiments. In addition, One-Color measurements alone can reconstruct expression ratios without loss in precision or accuracy. We conclude that both methods are adequate options in large-scale projects where the amount of a common reference RNA pool is usually restrictive.

Genomic sequence of the pathogenic and allergenic filamentous fungus Aspergillus fumigatus

Aspergillus fumigatus is exceptional among microorganisms in being both a primary and opportunistic pathogen as well as a major allergen. Its conidia production is prolific, and so human respiratory tract exposure is almost constant. A. fumigatus is isolated from human habitats and vegetable compost heaps. In immunocompromised individuals, the incidence of invasive infection can be as high as 50% and the mortality rate is often about 50% (ref. 2). The interaction of A. fumigatus and other airborne fungi with the immune system is increasingly linked to severe asthma and sinusitis. Although the burden of invasive disease caused by A. fumigatus is substantial, the basic biology of the organism is mostly obscure. Here we show the complete 29.4-megabase genome sequence of the clinical isolate Af293, which consists of eight chromosomes containing 9,926 predicted genes. Microarray analysis revealed temperature-dependent expression of distinct sets of genes, as well as 700 A. fumigatus genes not present or significantly diverged in the closely related sexual species Neosartorya fischeri, many of which may have roles in the pathogenicity phenotype. The Af293 genome sequence provides an unparalleled resource for the future understanding of this remarkable fungus.

[12] Genomic DNA as a General Cohybridization Standard for Ratiometric Microarrays

Feature variability on ratiometric microarrays is accommodated by simultaneous cohybridization of a labeled reference standard with a labeled experimental sample. An optimal reference standard would provide full and equal representation for all array features from a given genome so that it would function on any array, would represent all features with similar signal intensity, and would be highly reproducible-both technically and biologically-from preparation to preparation and laboratory to laboratory. A low cost and a good shelf life are also highly desirable. Finally, providing for straightforward recovery of RNA prevalence information and for integration of data across multiple, initially unrelated studies would be significant advances over current methods. For virtually all ratiometric array studies published to date the reference standard has been some kind of RNA sample assembled from a number of different cell lines, tissues, or experimental time points. These RNA references fall short of the desired universality, uniformity, and reproducibility criteria, which then affect data quality and integration across studies. Also, the various mixed RNA standards cannot be used to derive RNA prevalence information from an experimental sample. In contrast, genomic DNA is a natural choice to meet all the criteria, although it has not yet been widely exploited for eukaryotic array experiments. Principal stumbling blocks have been achieving high enough absolute signals for large mammalian and plant genomes and finding a way to stabilize labeled DNA so that it can be stored and used with ease. This chapter describes two genomic DNA-labeling methods that make it possible to use genomic DNA as a universal microarray cohybridization standard. The indirect labeling method permits production of a large quantity of a stable genomic DNA standard that can then be quality tested and stored frozen. This optimizes experimental consistency and significantly improves ease of use. This chapter also shows that the genomic DNA reference standard can deliver RNA prevalence measurements from ratiometric array platforms.

Bacterial genome adaptation to niches: divergence of the potential virulence genes in three Burkholderia species of different survival strategies

BACKGROUND

Two closely related species Burkholderia mallei (Bm) and Burkholderia pseudomallei (Bp) are serious human health hazards and are potential bio-warfare agents, whereas another closely related species Burkholderia thailandensis (Bt) is a non-pathogenic saprophyte. To investigate the genomic factors resulting in such a dramatic difference, we first identified the Bm genes responsive to the mouse environment, and then examined the divergence of these genes in Bp and Bt.

RESULTS

The genes down-expressed, which largely encode cell growth-related proteins, are conserved well in all three species, whereas those up-expressed, which include potential virulence genes, are less well conserved or absent notably in Bt. However, a substantial number of up-expressed genes is still conserved in Bt. Bm and Bp further diverged from each other in a small number of genes resulting from unit number changes in simple sequence repeats (ssr) in the homologs.

CONCLUSION

Our data suggest that divergent evolution of a small set of genes, rather than acquisition or loss of pathogenic islands, is associated with the development of different life styles in these bacteria of similar genomic contents. Further divergence between Bm and Bp mediated by ssr changes may reflect different adaptive processes of Bm and Bp fine-tuning into their host environments.

Defining best practice for microarray analyses in nutrigenomic studies

Microarrays represent a powerful tool for studies of diet-gene interactions. Their use is, however, associated with a number of technical challenges and potential pitfalls. The cost of microarrays continues to drop but is still comparatively high. This, coupled with the complex logistical issues associated with performing nutritional microarray studies, often means that compromises have to be made in the number and type of samples analysed. Additionally, technical variations between array platforms and analytical procedures will almost inevitably lead to differences in the transcriptional responses observed. Consequently, conflicting data may be produced, important effects may be missed and/or false leads generated (e.g. apparent patterns of differential gene regulation that ultimately prove to be incorrect or not significant). This is likely to be particularly true in the field of nutrition, in which we expect that many dietary bioactive agents at nutritionally relevant concentrations will elicit subtle changes in gene transcription that may be critically important in biological terms but will be difficult to detect reliably. Thus, great care should always be taken in designing and executing microarray studies. This article seeks to provide an overview of both the main practical and theoretical considerations in microarray use that represent potential sources of technical variation and error. Wherever possible, recommendations are made on what we propose to be the best approach. The overall aims are to provide a basic framework of advice for researchers who are new to the use of microarrays and to promote a discussion of standardisation and best practice in the field.

Suitability of stratagene reference RNA for analysis of lymphoid tissues

We evaluated a lymphoid RNA standard prepared in our laboratory for spotted microarrays against the Universal Human Reference standard from Stratagene. Our goal was to determine if the Stratagene standard, which contains only two lymphoid cell lines out of a pool of 10 human cancer cell lines, had acceptable gene coverage to serve as a comprehensive standard for gene expression profiling of lymphoid tissues. Our lymphoid standard was prepared from thymus, spleen, tonsil, and cell lines representing immature B cells, plasma cells, and natural killer (NK) cells, thus covering the entire spectrum of lymphoid cells and most stromal elements present in specialized lymphoid tissues. The two standards were co-hybridized on oligonucleotide microarrays containing 17,260 genes, and both had fluorescence intensities above background for approximately 85% of the genes. Despite the limited representation of lymphoid cells in the Stratagene standard, only 4.2% genes exhibited expression differences greater than 2-fold including only 0.35% with differences greater than 4-fold. Although the lymphoid standard reflected a more comprehensive representation of immune system-associated genes, the Stratagene standard has the advantage of being commercially available, enabling easier comparison across laboratories and allowing comparative studies across a long period of time.

An analysis of the use of genomic DNA as a universal reference in two channel DNA microarrays

Background

DNA microarray is an invaluable tool for gene expression explorations. In the two-dye microarray, fluorescence intensities of two samples, each labeled with a different dye, are compared after hybridization. To compare a large number of samples, the 'reference design' is widely used, in which all RNA samples are hybridized to a common reference. Genomic DNA is an attractive candidate for use as a universal reference, especially for bacterial systems with a low percentage of non-coding sequences. However, genomic DNA, comprising of both the sense and anti-sense strands, is unlike the single stranded cDNA usually used in microarray hybridizations. The presence of the antisense strand in the 'reference' leads to reactions between complementary labeled strands in solution and may cause the assay result to deviate from true values.

Results

We have developed a mathematical model to predict the validity of using genomic DNA as a reference in the microarray assay. The model predicts that the assay can accurately estimate relative concentrations for a wide range of initial cDNA concentrations. Experimental results of DNA microarray assay using genomic DNA as a reference correlated well to those obtained by a direct hybridization between two cDNA samples. The model predicts that the initial concentrations of labeled genomic DNA strands and immobilized strands, and the hybridization time do not significantly affect the assay performance. At low values of the rate constant for hybridization between immobilized and mobile strands, the assay performance varies with the hybridization time and initial cDNA concentrations. For the case where a microarray with immobilized single strands is used, results from hybridizations using genomic DNA as a reference will correspond to true ratios under all conditions.

Conclusion

Simulation using the mathematical model, and the experimental study presented here show the potential utility of microarray assays using genomic DNA as a reference. We conclude that the use of genomic DNA as reference DNA should greatly facilitate comparative transcriptome analysis.

Standardizing global gene expression analysis between laboratories and across platforms

To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms, and methods to accommodate this variability. RNA expression data were generated in seven laboratories, which compared two standard RNA samples using 12 microarray platforms. At least two standard microarray types (one spotted, one commercial) were used by all laboratories. Reproducibility for most platforms within any laboratory was typically good, but reproducibility between platforms and across laboratories was generally poor. Reproducibility between laboratories increased markedly when standardized protocols were implemented for RNA labeling, hybridization, microarray processing, data acquisition and data normalization. Reproducibility was highest when analysis was based on biological themes defined by enriched Gene Ontology (GO) categories. These findings indicate that microarray results can be comparable across multiple laboratories, especially when a common platform and set of procedures are used.

Development of a new reference standard for microarray experiments

Often microarray studies require a reference to indirectly compare the samples under observation. References based on pooled RNA from different cell lines have already been described (here referred to as RNA-R), but they usually do not exhaustively represent the set of genes printed on a chip, thus requiring many adjustments during the analyses. A reference could also be generated in vitro transcribing the collection of cDNA clones printed on the microarray in use (here referred to as T3-R). Here we describe an alternative and simpler PCR-based methodology to construct a similar reference (Chip-R), and we extensively test and compare it to both RNA-R and T3-R. The use of both Chip-R and T3-R dramatically increases the number of signals on the slides and gives more reproducible results than RNA-R. Each reference preparation is also evaluated in a simple microarray experiment comparing two different RNA populations. Our results show that the introduction of a reference always interferes with the analysis. Indeed, the direct comparison is able to identify more up- or down-regulated genes than any reference-mediated analysis. However, if a reference has to be used, Chip-R and T3-R are able to guarantee more reliable results than RNA-R.

Structural flexibility in the Burkholderia mallei genome

The complete genome sequence of Burkholderia mallei ATCC 23344 provides insight into this highly infectious bacterium's pathogenicity and evolutionary history. B. mallei, the etiologic agent of glanders, has come under renewed scientific investigation as a result of recent concerns about its past and potential future use as a biological weapon. Genome analysis identified a number of putative virulence factors whose function was supported by comparative genome hybridization and expression profiling of the bacterium in hamster liver in vivo. The genome contains numerous insertion sequence elements that have mediated extensive deletions and rearrangements of the genome relative to Burkholderia pseudomallei. The genome also contains a vast number (>12,000) of simple sequence repeats. Variation in simple sequence repeats in key genes can provide a mechanism for generating antigenic variation that may account for the mammalian host's inability to mount a durable adaptive immune response to a B. mallei infection.

Genomic DNA as a cohybridization standard for mammalian microarray measurements

A persistent design problem for ratiometric microarray studies is selecting the 'denominator' RNA cohybridization standard. The ideal standard should be readily available, inexpensive, invariant over time and from laboratory to laboratory, and should represent all genes with a uniform signal. RNA references (both commercial 'universal' and experiment--specific types), fall short of these goals. We show here that mouse genomic DNA is a reliable microarray cohybridization standard which can meet these criteria. Genomic DNA was superior in universality of coverage (>98% of genes from a 16,000 feature mouse 70mer microarray) to the Stratagene Universal Mouse Reference RNA standard. Ratios for genes in very low abundance in the Stratagene standard were more unstable with the Stratagene standard than with genomic DNA. Genes with mid-range, and therefore presumably optimal RNA denominator values, showed comparable reproducibility with both standards. Inferred ratios made between two different experimental RNAs using a genomic DNA standard were found to correlate well with companion, directly measured ratios (Spearman correlation coefficient = 0.98). The advantage in array feature coverage of genomic DNA will likely increase as newer generation microarrays include genes which are expressed exclusively in minor tissue or developmental domains that are not represented in mixed tissue RNA standards.

Absolute expression values for mouse transcripts: re-annotation of the READ expression database by the use of CAGE and EST sequence tags

The RIKEN expression array database (READ) provides comprehensive gene expression data for the mouse, which were obtained as relative values from microarray double-staining experiments with E17.5 mRNA as common reference. To assign absolute expression values for mouse transcripts within READ, we applied the E17.5 reference sample to CAGE (cap analysis of gene expression) and expressed sequence tag (EST) high-throughput tag sequencing. Newly assigned values within the READ database were validated by comparison to expression data from serial analysis of gene expression, CAGE and EST experiments. These experiments confirmed the great significance of the absolute expression values within the improved READ database. The new Absolute READ database on absolute expression data is available under.

Standardization of protocols in cDNA microarray analysis

Systematic variations can occur at various steps of a cDNA microarray experiment and affect the measurement of gene expression levels. Accepted standards integrated into every cDNA microarray analysis can assess these variabilities and aid the interpretation of cDNA microarray experiments from different sources. A universally applicable approach to evaluate parameters such as input and output ratios, signal linearity, hybridization specificity and consistency across an array, as well as normalization strategies, is the utilization of exogenous control genes as spike-in and negative controls. We suggest that the use of such control sets, together with a sufficient number of experimental repeats, in-depth statistical analysis and thorough data validation should be made mandatory for the publication of cDNA microarray data.